Processes such as semiconductor processing processes include multiple steps over an interval of time. A process may include a transition from a first step to a second step. Time-series data is data collected over the interval of time, including the transition (e.g., the time-series transition). Typically, statistical methods (e.g., statistical process control (SPC)) are utilized to analyze sensor data for semiconductor manufacturing processes. However, SPC and other statistical methods of monitoring processes are not capable of monitoring time-series transitions. Statistical methods cannot detect short-time signal perturbations in data received from sensors over time. Statistical methods also provide false positives (e.g., that an entire signal does not match a target signal because a minimal portion of the signal is outside of a guard band) and do not allow for adjustment of the sensitivity of anomaly detection.